Prognosis And Health Management Datasets

A collection of datasets for Prognosis and Health Management (PHM) applications. The repository was created by hustcxl and last updated in April 2020. It focuses on data for predicting failures and monitoring the health of systems.

Use Cases

• Predict remaining-useful-life from sensor time-series data using regression models.
• Classify failure-modes from vibration or acoustic-emission features using supervised learning.
• Detect anomalies in operational-parameters like temperature or pressure for early fault warning.
• Benchmark PHM algorithms using provided run-to-failure or degradation datasets.

Strengths

• Repository contains multiple distinct datasets for PHM benchmarking.
• Focuses on a specialized domain with clear application to industrial AI.

Limitations

• No specific row counts, column names, or sample data are provided for evaluation.
• The data's original collection methodology and time range are unspecified.
• Last update was in 2020, indicating potential staleness for current techniques.

Provenance

Source

GitHub repository by hustcxl.

Collection Method

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Time Range

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Freshness

Last updated 2020-04-30.

Geography

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